Wireless communication systems serving stationary and mobile wireless subscribers are currently in wide use and are very popular with consumers. Numerous system layouts and communications protocols have been developed to provide coverage in such wireless communication systems.
The wireless communications channels between the transmit device, or transmission unit, (transmitter) and receive device, or receiver unit, (receiver) are inherently variable. Thus, their quality parameters fluctuate in time. Under favorable conditions, wireless channels exhibit good communication parameters, e.g., large data capacity, high signal quality, high spectral efficiency and throughput. Under these favorable conditions, significant amounts of data can be transmitted via the channel reliably. However, as the channel changes in time, the communication parameters also change. Under altered conditions, former data rates, coding techniques and data formats may no longer be possible. For example, when the channel performance is degraded, the transmitted data may experience excessive corruption yielding unacceptable communication parameters. For instance, transmitted data can exhibit excessive bit-error rates or packet error rates. The degradation of the channel can be due to a multitude of factors such as general noise in the channel, multi-path fading, loss of line-of-sight path, excessive Co-Channel Interference (CCI) and other factors.
In mobile communications systems, a variety of factors may cause signal degradation and corruption. These include interference from other cellular users within or near a particular cell. Another source of signal degradation is multipath fading, wherein the received amplitude and phase of a signal varies over time. Channel state information at the receiver is usually obtained through a training sequence to offset channel degradation. However, training sequences are an expensive commodity when bandwidth is in demand, because they are typically recurring transmission overhead that does not communicate data that is useful to the end users of the communication system. Limiting or eliminating training sequences necessarily frees bandwidth for other uses.
It has been shown that in a Rayleigh flat-fading environment, the capacity of a multiple-input/multiple-output (MIMO) communication system is increased as compared to a communication system using a single transmit and a single receive antenna. This is because multipath communication offers advantages that can be exploited to increase data rates. Specifically, data capacity increases linearly with the smaller of the number of transmit and receive antennas, provided that the fading coefficients for the multiple sub-channels between transmit and receive antennas are known at the receiver. In a slowly fading channel, where the fading coefficients remain approximately constant for many symbol intervals, the transmitter can send training signals that allow the receiver to accurately estimate the fading coefficients.
In practice, due to the necessarily finite length of the training sequence, there will always be some errors in the channel estimates. In order to maintain a given data rate, more rapidly fading channels would result in shorter training sequences, all other parameters being equal. This is because the data desired by a user would crowd out the training sequence, resulting in even less reliable channel estimates. Employing multiple transmit antennas compounds the above problem by requiring longer training sequences for the same estimation performance, since there are more sub-channels to estimate.
A typical assumption in designing optimal codes and signal constellations is known channel parameters at the receiver. That assumption is especially inappropriate in communication systems with multiple transmit antennas. For fast fading channels where the fading coefficients vary too fast to allow a long training period, or for MIMO systems where very long training sequences are required to accurately train all of the possible channels from the transmitter to the receiver, obtaining an accurate estimate of the channel at the receiver may not always be possible. For the above situations where only a rough estimate of the channel state is available at the receiver, existing signal constellations (e.g. PSK, QAM) and multiple-antenna techniques (e.g., V-BLAST, orthogonal transmit diversity), are no longer optimal because they are designed with the assumption of perfect channel state information at the receiver.
In the presence of channel estimation errors (partially coherent systems), signal constellations which are designed using the statistics of the estimation error are more desirable than those designed for perfect channel state information at the receiver.
Currently, PSK (phase shift key) signal constellations are sometimes used in the case of unreliable channel estimates at the receiver for a single antenna system, because PSK constellations are not sensitive to the errors in the estimates of channel amplitude. However, PSK constellations exhibit poor performance for high rate applications, which require larger signal sets. For a multiple antenna system, conventional constellations (PSK or QAM) are sometimes used in conjunction with some multiple-antenna technique such as V-BLAST or transmit diversity. However, theses approaches assume perfect channel state information at the receiver, which is often an invalid assumption as described above. MIMO communication systems using conventional constellations consequently suffer severe performance degradation in the presence of estimation errors as low as a few percent.
What is needed in the art is a new type of signal constellation tailored for the unique challenges of a communication system using multiple transmit and/or multiple receive antennas. Such a constellation system would require short or no training sequences, yet provide acceptable error rates despite imperfect channel state knowledge at the receiver. Ideally, advancement in the art is best served by a technique for designing such a signal constellation to facilitate further refinements.